1. Field of the Invention
The present invention relates generally to the estimation of the position and orientation of a three-dimensional object in a two-dimensional image taken by an imaging device such as a camera, and more specifically to a pose estimation method and apparatus for estimating the pose of an object using the three-dimensional shape of a target object and its surface reflectivity or color information.
2. Description of the Related Art
Various methods are known in the art for estimating the position and orientation of a three-dimensional object in a two-dimensional image. One approach is the analytic solution of the n-point perspective problem, which concerns the determination of the position and orientation (pose) of a camera with respect to a three-dimensional object, when n points of the object corresponds to n points of a two-dimensional image. The issue of computations associated with pose estimation is described in documents such as, “An Analytic Solution for the Perspective 4-point Problem”, Radu Horaud et al., Computer Vision, Graphics and Image Processing, 47, pp. 33-44 (1989) and “Linear N≧4-Point Pose Determination”, Long Quan and Zhongdan Lan, Proceedings of IEEE International Conference Computer Vision, 6, pp. 778-783 (1998). The analytic solution of the n-point perspective problem is the problem of finding the best pose from a plurality of candidates that were calculated from feature points of an image object in an input image and the registered positions of corresponding feature points of a three-dimensional target object. If correspondence occurs at least three feature points, a maximum of four pose candidates can be calculated. Since the amount of positional information contained in the three-point features is not sufficient to uniquely determine the best candidate, correspondences are usually required for at least four feature points. Pose candidates are first calculated from three of the at least four points, and a best one is selected from the candidates when the remainder point is calculated. However, insofar as an error is contained in the positional information there are no pose parameters where correspondence occurs at all feature points. Since this type of error is unavoidable and no information other than the position data is used, the analytic solution of n-point perspective problem can be considered as an error minimization technique such as the least squares algorithm. If the target object has jagged edges or an ambiguous shape or has no particular surface features, the error increases and detectable features decrease.
Japanese Patent Publication 2001-283229 discloses another technique in which errors are designed into the feature points position data and pose determination involves the use of only those feature points where errors are small. According to this technique, a set of arbitrarily combined three feature points is selected, and a pose candidate calculation is performed to obtain pose candidates while correcting the position of each selected point. The pose candidates are then fitted to all feature points, and the best candidate is chosen that yields a minimum error.
Japanese Patent Publication 2000-339468 discloses a technique in which an object is subjected to illumination at different angles. A pair of 3D shapes of the same object as seen from a given viewing angle is produced, and these 3D shapes are searched for corresponding feature points. The detected feature points are used to estimate the difference between the two 3D shapes. This technique can be used for pose estimation by producing an input image from one of the 3D shapes.
Another prior art technique disclosed in Japanese Patent Publication 1999-051611 relates to the detection of contour lines of an image object such as a cylinder. The detected contour lines are compared with stored contour line data of a 3D model to correct calculated pose parameters.